Low-Cost Data Acquisition System for Automotive Electronic Control Units

Area of Science:

• Automotive Engineering
• Embedded Systems
• Data Science

Background:

• Vehicle testing and validation are critical for automotive development, ensuring safety and performance.
• Existing commercial solutions are often costly, limited in connectivity, and require PC dependency.

Purpose of the Study:

• To present an innovative, low-cost, IoT-based system for intelligent vehicle data acquisition during on-road testing.
• To offer an alternative to expensive and restrictive commercial testing systems.

Main Methods:

• Integration of low-cost hardware for data acquisition with an IoT server.
• Near real-time data collection and transmission.
• Application of artificial intelligence (AI) algorithms for data processing and failure detection.

Main Results:

• The proposed system achieves a comparable data acquisition rate to commercial systems.
• The system is significantly more cost-effective, up to 13 times cheaper.
• Advanced features include near real-time intelligent data processing and accelerated error correction.

Conclusions:

• The developed IoT system provides a viable, cost-effective, and feature-rich alternative for vehicle data acquisition.
• It enhances the efficiency of identifying and rectifying vehicle errors and failures during the testing phase.